The Affects of the Foot Conditions on the Homeless Population
Bibliographic record
Abstract
The research is attempting to acknowledge and explain the impact, if any, on homeless individuals not wearing socks. The curiosity for this study started on December 25th, 2018 when my family and I were volunteering at a homeless shelter in South Florida. After having numerous conversations with homeless individuals, I was informed on how they do not have enough pairs of socks to keep their feet in a healthy condition. Thus, I decided to initiate a sock drive to improve the lives of those who are homeless. This study is looking at a series of articles that are reviewing the different foot issues amongst the homeless community but are looking to see if socks play a role in the feet developing any foot diseases. It was hypothesized that homeless individuals will be at greater risk for foot disease if they live outside and have improper footwear. The objective of the study sought to review the current literature on the lack of socks for those who are homeless. Between the United States and Canada, it is estimated that nearly 700,000 individuals are homeless in a 2016 report. Of the 700,000 there are roughly two-thirds of this population that have some type of disease with their foot (To and Brothers, 2017). Majority of people who perform a good deed, such as give away old clothes or shoes, very seldomly donate socks according to the company Bombas socks. Throughout the course of my time volunteering, I have witnessed several homeless individuals wear shoes but not socks. Due to uncomfortableness, the individuals remove their shoes and it is very eye opening to observe their feet. Homeless shall be defined as “having no home or permanent place of residence” as per the Merriam-Webster's dictionary. The study was reported based on guidelines recommended by the Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) of 125 studies related to homelessness and foot diseases and disorders. Literature searches were carried out on PubMed, Google Scholar, and ScienceDirect. With an evidentiary table, the characteristics of the studies included in the meta-analysis (n = 100 studies) are presented. This analysis suggests that not wearing the appropriate foot protection (shoes and/or socks) leads to an increase in foot diseases and disorders among the homeless.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".